Dave Hendry, Regional Sales Director, Fanplayr
The decision by Google and the other major browser companies to axe third-party cookies deserves close attention from financial services companies.
Coming fully into force next year, the move will effectively end the traditional supply of data that has enabled personalisation, optimised website interactions and driven internet advertising. A company will no longer be able to build a picture of individuals’ habits and preferences by using a cookie to track where its web visitors go once they have left its site.
The reason the big browser companies have called a halt to third-party cookies is because of their fears about infringement of legislation such as the EU’s GDPR (General Data Protection Regulation) and the CCPA (California Consumer Privacy Act) in California.
In theory, the end of third-party cookies has come just at the wrong time, as millions of people shift to online or mobile banking in large numbers. In the UK, for example, more than three-quarters of Britons now use online banking and 14 million use digital-only banks.
A major opportunity to improve web interactions with newer technology
It seems drastic, but it is actually an opportunity for financial organisations to improve how they interact with expanding numbers of web visitors and customers using newer technologies. Behavioural analytics driven by AI, for example, is a technology that offers far superior, real-time capabilities when compared with the conventional use of third-party cookie data. These analytics solutions use customer behaviour data generated by financial organisations’ own website domains and where available, correlate it with data from customers’ transaction histories.
The result is a solution that is faster, more accurate and responsive than conventional technology relying on cookie data owned and stored by third-party organisations. Instead of rigid profiling and personalisation, behavioural analytics enables real-time interactions based on a more dynamic picture of how an individual’s requirements are changing.
Using a first-party cookie of the type employed by Facebook, behavioural analytics solutions examine a customer’s browsing characteristics including time on site, speed of movement and page views, as well as more obvious features such as interest in specific products. Historical data added to the analysis includes what customers did on previous visits and the interval between those visits, establishing patterns where possible.
Segmentation for better targeting
Segmentation allows a bank to identify customers as soon as they arrive on its site, according to whether they are a new or existing customer. Their behaviour then indicates what they want.
Knowing what customers are interested in is important. Customers visit financial services websites for a host of reasons – from seeking information, to opening accounts or exploring loans and mortgage offers. They may also want advice about investments and savings, pensions or small business finance. Almost all of these requirements involve quite complex mental processes which financial organisations can influence while consumers are on their sites.
Hubs that make insights actionable
Collecting the data is not difficult – the skill is in making it actionable in an effective way, replicating the ability of a perceptive employee to read a customer’s state of mind. Banks can do this by setting up a behavioural analytics hub to understand what a customer’s behaviour means and how it can be optimised.
Using customised parameters, the hub will, for instance, trigger a screen notification that prompts the web visitor to fill in a form requesting an appointment. In the case of existing customers, the technology can correlate health insurance offers with spending on fitness, and, in general, savings and investment recommendations can be tailored to the client’s concerns or goals as revealed by their navigation of the website or mobile app.
Banks can set up analytics to see when consumers are behaving in a way that indicates they about to leave the website, allowing them to intervene with a notification that could include an offer. This provides a positive outcome and avoids the blanket use of offers that undermines profitability.
It is a more sophisticated and personalised approach that avoids annoying pop-ups or recommendations that fail to match individual preferences. As part of a single AI-powered segmentation platform, the technology enables banks to personalise marketing content in SMS messages and emails sent to consumers (who consent), which deliver far better results through precise targeting.
Solutions for last-mile interaction in the open banking era
The single platform approach also has another major advantage. It is much easier to implement and far more efficient and streamlined compared with separate solutions for different parts of the customer journey.
The benefits of using AI-powered segmentation solutions should be part of the financial sector’s broader strategy to transform its systems for the open banking era as we approach the end of third-party cookies. It is almost a commonplace to say that banks continue to struggle with the complexity of their systems, undermining their ability to deliver a high-quality last mile for consumers. This is one headache they can now resolve without huge disruption or investment.
The alternative is to risk losing track of customers. Behavioural analytics, by contrast, will deliver new insights into customers that are better than third-party cookie data, being more accurate and actionable in real time. Financial services organisations need to employ the latest advances in AI-powered behavioural analytics if they are serious about providing a slick and personalised service to customers that doesn’t break the bank.
